Table 3.
Characteristics of included studies (n = 22) about mediation between socioeconomic status (SES) and preterm birth
| Paper | Design | Country | Sample Size and Characteristics | Study Period | Mediation Analysis Approach | Measure of SES | Quality Score (/13) |
|---|---|---|---|---|---|---|---|
| Poulsen et al. (2019) [33] | Cohort | Denmark | 77,020 – National birth cohort (whole) | NS | Difference method using risk differences from linear regression | Maternal education: Short (≤ lower secondary) to long (degree; reference) | 10 |
| Netherlands | 4,508 – Rotterdam birth cohort (whole) | NS | |||||
| Norway | 78,267 – National birth cohort (whole) | NS | |||||
| Ross et al. (2019) [34] | Cohort | United States (US) | 718,952 –Californian birth cohort (whole) | 2007–2012 | Product of coefficients/ Path analysis using Lavaan Package | Maternal education: At most high-school to more than high school (reference) | 9 |
| Dolatian et al. (2014) [35] | Cohort | Iran | 500 – Random sample of pregnant women from stratified sample of four Tehran hospitals | 2011–2012 | Product of coefficients/ Path analysis using Lisrel Software | Income | 9 |
| Clayborne et al. (2017) [36] | Cohort | Canada | 2,068 – Sample of pregnant women from Calgary and Edmonton Metropolitan Regions | 2008–2012 | Product of coefficients using PROCESS macro | Neighbourhood SES | 8 |
| Dooley (2009) [37] [PhD thesis] | Cross-sectional | US | 28,793 – Hamilton County, Ohio, birth cohort (whole) | 2001–2003 | Product of coefficients/ Path analysis of multilevel modelling using Mplus | Neighbourhood concentrated disadvantage | 8 |
| Mehra et al. (2019) [38] | Cohort | US | 138,494 – National convenience sample (retrospective) of births from all states using health insurance data | 2011 | Product of coefficients/ Path analysis of multilevel modelling using Mplus | Neighbourhood SES: most deprived quarter to least deprived (reference) | 8 |
| Meng et al. (2013) [39] | Cross-sectional | Canada | 90,500—All births (including multiple) at three Ontario province public health units | 2000–2008 | Product of coefficients of multilevel modelling using both linear and logistic regression | Neighbourhood SES | 8 |
| Mirabzadeh et al. (2013) [40] | Cohort | Iran | 500 – Random sample of pregnant women from stratified sample of four Tehran hospitals | 2012–2013 | Product of coefficients/ Path analysis using Lisrel Software | Composite comprising: maternal and spousal education, persons and cost/household area, car, computer | 8 |
| Misra et al. (2001) a[41] | Cross-sectional | US | 735 – Urban university hospital sample of births to black mothers: drug users, women without prenatal care, and a systematic sample of the rest | 1995–1996 | Difference method using logistic regression | Lack of time and money | 8 |
| Nkansah-Amankra et al. (2010) [42] | Cross-sectional | US | 8,064 – South Carolina state, stratified systematic sample of births | 2000–2003 | Difference method using multilevel logistic modelling | Neighbourhood SES: Proportion of residents in poverty | 8 |
| Räisänen et al. (2013) [43] | Cross-sectionalb | Finland | 1,390,742 – National birth cohort (whole) | 1987–2010 | Difference method using logistic regression | Maternal occupation; blue collar relative to upper white collar (reference) | 8 |
| Ahern et al. (2003) [44] | Case–Control | US | 1,496 cases + controls – A San Francisco hospital based sample of births: All preterm plus random selections of full-term, stratified by African American and White | 1980–1990 | Difference method using multilevel logistic modelling | Neighbourhood context | 7 |
| Amegah et al. (2013) [45] | Cross-sectional | Ghana | 559 – Cape Coast’s four main healthcare facilities, random sample weighted by hospital or urban centre | 2011 | Difference method: Generalised linear model using Poisson Distribution and log link | Level of monthly income: low to upper middle and high (reference) | 7 |
| van den Berg et al. (2012) [46] | Cohort | Netherlands | 3,821 – Amsterdam birth cohort (Dutch-only) (whole) | 2003–2004 | Difference method using logistic regression | Maternal education: years of education after primary school, low (< 6) to high (> 10; reference) | 7 |
| Morgen et al. (2008) [47] | Cohort | Denmark | 38,131 primiparous & 37,849 multiparous – National birth cohort | 1996–2002 | Difference method using Cox regression | Maternal education; < 10 years to > 12 years (reference) | 7 |
| Gisselmann and Hemström (2008) [48] | Cross-sectional | Sweden | 356,887 – National birth cohort (whole) | 1980–1985 | Difference method using logistic regression | Maternal occupation: Unskilled manufacturing manuals to middle non-manuals (reference) | 7 |
| Niedhammer et al. (2012) [49] | Cohort | Republic of Ireland | 913 – Random sample of pregnant women (Irish-only) from two hospitals (urban and rural) | 2001–2003 | Difference method using Cox Regression | Maternal education: lower than to higher than secondary (reference) | 7 |
| Jansen et al. (2009) [50] | Cohort | Netherlands | 3,830 – Rotterdam birth cohort (whole) | 2002–2006 | Difference method using logistic regression | Maternal education: low (< 4 years general secondary) to high (Master degree, PhD; reference) | 7 |
| Quispel et al. (2014) a[51] | Cohort | Netherlands | 1,013 – Rotterdam, Apeldoorn, Breda: Random samples of pregnant women from primary, secondary, tertiary care | 2009–2011 | Difference method using logistic regression | Maternal education: low to moderate (reference) | 6 |
| Gissler et al. (2003) [52] | Cross-sectional | Finland | 548,913 – National birth cohort (whole) | 1991–1999 | Difference method using logistic regression | Maternal occupation: blue collar to upper white collar (reference) | 6 |
| Gray et al. (2008) [53] | Cohort | Scotland | 400,752 – National (hospital) birth cohort (whole) | 1994–2003 | Difference method using logistic regression | Neighbourhood SES: most deprived fifth to least deprived (area-based) (reference) | 6 |
| de Oliveira et al. (2019) [54] | Case–Control | Brazil | 296 cases + 329 controls – Londrina sample of hospital births (including multiple) | 2006–2007 | Structural equation modelling | Socioeconomic vulnerability | 4 |
NS not stated
a Not specified if Misra et al. (2001) [41] and Quispel et al. (2014) [51] excluded multiple births. Meng et al. (2013) [39] and de Oliveira et al. (2019) [54] included multiple births. All other studies excluded multiple births
b despite being labelled as a case–control study
Ordered by Quality Score